Understand the social sentiment of your brand, product or service while monitoring online conversations.
Sentiment Analysis is contexual mining of text which identifies and extracts subjective information in source material.
Sentiment analysis API provides a very accurate analysis of the overall emotion of the text content incorporated from sources like Blogs, Articles, forums, consumer reviews, surveys, twitter etc. Sentiment Analysis can be widely applied to reviews and social media for a variety of applications, ranging from marketing to customer service.
It uses Long Short Term Memory (LSTM) algorithms to classify a text blob's sentiment into positive and negative. LSTMs model sentences as chain of forget-remember decisions based on context. It is trained on social media data and news data differently for handling casual and formal language. We also have trained this algorithm for various custom datasets for different clients.
With advancement of social media, tracking and monitoring each conversation on these channels have become very important. Sentiment analysis can help in analyzing the tone or emotion of social mentions related to business, brand or product
Deeper insights obtained from customer reviews, social conversations and online forums can be very helpful in improving brand perception. Identifying and actioning feedback using sentiment analysis can help in providing consumer a superior experience and retaining existing ones.
Influencers act as an impetus to their audience and define future trends. Knowing advocates and detractors of your brand using sentiment analysis and communicating with them can be a key strategy for increasing brand awareness and engagement.
With data flooding around on web, gaining actionable insights can get difficult. Sentiment analysis can drastically reduce the time spent on research and manual effort required to understand these data
Highly accurate sentiment classification on social media data (misspellings, emojis, slangs etc.)
State of the art technology to provide accurate results in realtime.
Can be trained on custom dataset to obtain similar accuracy and performance.